U.S. patent number 8,868,443 [Application Number 13/050,769] was granted by the patent office on 2014-10-21 for targeted incentive actions based on location and intent.
This patent grant is currently assigned to eBay Inc.. The grantee listed for this patent is Ryan Melcher, Robert Dean Veres, Steve Yankovich. Invention is credited to Ryan Melcher, Robert Dean Veres, Steve Yankovich.
United States Patent |
8,868,443 |
Yankovich , et al. |
October 21, 2014 |
Targeted incentive actions based on location and intent
Abstract
A method and a system offer an incentive to a user of a mobile
device based on a geographic location of the mobile device and the
intent of the user. A processor-implemented location identification
module determines the geographic location of the mobile device of
the user. A processor-implemented item identification module
identifies an item specified by the user at the geographic location
of the mobile device. A processor-implemented incentive module
offers an incentive from at least one merchant within a predefined
distance based on the identified item and the geographic location
of the mobile device.
Inventors: |
Yankovich; Steve (San Jose,
CA), Melcher; Ryan (Ben Lomond, CA), Veres; Robert
Dean (Evanston, IL) |
Applicant: |
Name |
City |
State |
Country |
Type |
Yankovich; Steve
Melcher; Ryan
Veres; Robert Dean |
San Jose
Ben Lomond
Evanston |
CA
CA
IL |
US
US
US |
|
|
Assignee: |
eBay Inc. (San Jose,
CA)
|
Family
ID: |
46829218 |
Appl.
No.: |
13/050,769 |
Filed: |
March 17, 2011 |
Prior Publication Data
|
|
|
|
Document
Identifier |
Publication Date |
|
US 20120239501 A1 |
Sep 20, 2012 |
|
Current U.S.
Class: |
705/14.1 |
Current CPC
Class: |
G06Q
30/0261 (20130101); H04W 4/029 (20180201); G06Q
30/0267 (20130101); G06Q 30/0235 (20130101); H04W
4/02 (20130101) |
Current International
Class: |
G06Q
30/00 (20120101) |
Field of
Search: |
;705/14.1 |
References Cited
[Referenced By]
U.S. Patent Documents
Other References
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|
Primary Examiner: Lastra; Daniel
Attorney, Agent or Firm: Schwegman Lundberg & Woessner,
P.A.
Claims
What is claimed is:
1. A system, comprising: a processor-implemented location
identification module configured to receive, from a mobile device
of a user, a communication that includes a picture of an item and
data that pertains to a location of the mobile device of the user,
the picture taken by the user with the mobile device of the user,
and determine, based on the communication, a geographic location of
the mobile device of the user; a processor-implemented item
identification module configured to identify the item based on the
picture of the item included in the communication; and a
processor-implemented incentive module configured to offer an
incentive from at least one merchant located within a predefined
distance from the geographic location of the mobile device, based
on the at least one merchant having the incentive for the
identified item and based on the geographic location of the mobile
device.
2. The system of claim 1 wherein the processor-implemented
incentive module further comprises: a processor-implemented local
merchant module configured to identify the at least one merchant
within the predefined distance with at least one incentive based on
the geographic location of the mobile device; a
processor-implemented incentive match module configured to
determine whether the item in the picture corresponds to an item
identified in the at least one incentive of the at least one
merchant within the predefined distance; and a
processor-implemented communication module configured to
communicate the at least one incentive from the at least one
merchant within the predefined distance to the mobile device.
3. The system of claim 1 wherein the processor-implemented
incentive module further comprises: a processor-implemented item
category module configured to determine a category of the item in
the picture; a processor-implemented incentive match module
configured to determine whether the category of the item in the
picture corresponds to a category of items identified in at least
one incentive of the at least one merchant within the predefined
distance; and a processor-implemented communication module
configured to communicate the at least one incentive of the
identified category of items from the at least one merchant within
the predefined distance to the mobile device.
4. The system of claim 1 wherein the processor-implemented
incentive module further comprises: a processor-implemented user
preference module configured to request from the user whether to
update a search distance preference for merchants; and a
processor-implemented local merchant module configured to identify
the at least one merchant having the incentive based on the updated
search distance preference.
5. The system of claim 1 wherein the processor-implemented
incentive module further comprises: a processor-implemented
incentive code module configured to communicate a code associated
with the at least one incentive to the mobile device, wherein the
code is valid for a predetermined period of time at the
corresponding merchant within the predefined distance.
6. The system of claim 1 wherein the processor-implemented location
identification module further comprises: a processor-implemented
triangulation service or a global positioning service (GPS)
configured to determine the location of the mobile device based on
a triangulation service or a GPS service; a processor-implemented
location input module configured to determine the location of the
mobile device based on a user input at the mobile device; a
processor-implemented location-dependent search term input module
configured to determine the location of the mobile device based on
a location- dependent search term user input at the mobile device;
a processor-implemented tag module configured to determine the
location of the mobile device based on a tag from the mobile
device, the tag associated with a unique geographic location.
7. The system of claim 1 wherein the processor-implemented item
identification module further comprises: a processor-implemented
text identification module configured to identify the item based on
a text input from the user at the geographic location of the mobile
device; a processor-implemented audio identification module
configured to identify the item based on an audio input from the
user at the geographic location of the mobile device; a
processor-implemented machine-readable symbol module configured to
identify the item based on a machine-readable symbol scanned by the
user at the geographic location of the mobile device; a
processor-implemented image identification module configured to
identify the item based on an image taken by the user at the
geographic location of the mobile device; and a
processor-implemented video identification module configured to
identify the item based on a video taken by the user at the
geographic location of the mobile device.
8. The system of claim 1 wherein the processor-implemented
incentive module further comprises: a processor-implemented user
preference module configured to generate a user preference setting,
the user preference setting comprising a user-defined search
distance preference.
9. The system of claim 1 wherein the processor-implemented
incentive module further comprises: a processor-implemented
incentive receiver module configured to receive attributes of
incentives from at least one merchant within the predefined
distance and store the attributes of the incentives in a database,
wherein the attributes of the incentives for an item comprises at
least one of a name attribute of the merchant within the predefined
distance, a name attribute of the item, a brand attribute of the
item, a model attribute of the item, a category tag of the item, a
sub-category tag of the item, a financial promotion attribute of
the item, and a financial promotion term attribute of the item.
10. The system of claim 1 wherein the incentive comprises a coupon,
a discount, or a recommendation.
11. A computer-implemented method comprising: receiving, from a
mobile device of a user, a communication that includes a picture of
an item and data that pertains to a location of the mobile device
of the user, the picture taken by the user with the mobile device
of the user; determining, based on the communication, a geographic
location of the mobile device of the user; identifying the item
based on the picture of the item included in the communication; and
offering an incentive from at least one merchant located within a
predefined distance from the geographic location of the mobile
device, based on the at least one merchant having the incentive for
the identified item and based on the geographic location of the
mobile device.
12. The computer-implemented method of claim 11 further comprising:
identifying at least one merchant within the predefined distance
with at least one incentive based on the geographic location of the
mobile device; determining whether the item in the picture
corresponds to an item identified in the at least one incentive of
the at least one merchant within the predefined distance; and
communicating the at least one incentive of the identified item
from the at least one merchant within the predefined distance to
the mobile device.
13. The computer-implemented method of claim 11 further comprising:
determining a category of the item in the picture; determining
whether the category of the item identified by the user corresponds
to a category of items identified in at least one incentive of the
at least one merchant within the predefined distance; and
communicating the at least one incentive of the identified category
of items from the at least one merchant within the predefined
distance to the mobile device.
14. The computer-implemented method of claim 11 further comprising:
requesting from the user whether to update a search distance
preference for merchants; and identifying the at least one merchant
having the incentive based on the updated search distance
preference.
15. The computer-implemented method of claim 11 further comprising:
communicating a code associated with the at least one incentive to
the mobile device, wherein the code is valid for a predetermined
period of time at the corresponding merchant within the predefined
distance.
16. The computer-implemented method of claim 11 further comprising:
determining the geographic location of the mobile device based on
at least one of a triangulation service or a global positioning
service (GPS) of the mobile device, a location input from the user
of the mobile device, a location-dependent search term input from
the user of the mobile device, and a tag associated with a unique
geographic location.
17. The computer-implemented method of claim 11 further comprising:
determining the item based on at least one of a text input from the
user of the mobile device, an audio input from the user of the
mobile device, a machine-readable symbol input from the user of the
mobile device, an image input from the user of the mobile device,
and a video input from the user of the mobile device.
18. The computer-implemented method of claim 11 wherein the
incentive is generated based on a preference setting of the user of
the mobile device, the preference setting comprising a user-defined
search distance preference.
19. The computer-implemented method of claim 11 further comprising:
receiving attributes of incentives from at least one merchant
within the predefined distance; storing the attributes of the
incentives in a database, wherein the attributes of the incentives
for an item comprises at least one of a name attribute of the
merchant within the predefined distance, a name attribute of the
item, a brand attribute of the item, a model attribute of the item,
a category tag of the item, a sub-category tag of the item, a
financial promotion attribute of the item, and a financial
promotion term attribute of the item.
20. The computer-implemented method of claim 11 wherein the
incentive comprises a coupon, a discount, or a recommendation.
21. A non-transitory computer-readable storage medium storing a set
of instructions that, when executed by a processor, causes the
processor to perform operations, comprising: receiving, from a
mobile device of a user, a communication that includes a picture
and data that pertains to a location of the mobile device of the
user, the picture taken by the user with the mobile device of the
user; determining, based on the communication, a geographic
location of the mobile device of the user; identifying the item
based on the picture of the item included in the communication; and
offering an incentive from at least one merchant located within a
predefined distance from the geographic location of the mobile
device, based on the at least one merchant having the incentive for
the identified item and based on the geographic location of the
mobile device.
22. The non-transitory computer-readable storage medium of claim 21
further comprising: identifying at least one merchant within the
predefined distance with at least one incentive based on the
geographic location of the mobile device; determining whether the
item in the picture corresponds to an item identified in the at
least one incentive of the at least one merchant within the
predefined distance; and communicating the at least one incentive
of the identified item from the at least one merchant within the
predefined distance to the mobile device.
23. The non-transitory computer-readable storage medium of claim 21
further comprising: determining a category of the item in the
picture; determining whether the category of the item in the
picture corresponds to a category of items identified in at least
one incentive of the at least one merchant within the predefined
distance; and communicating the at least one incentive of the
identified category of items from the at least one merchant within
the predefined distance to the mobile device.
24. The non-transitory computer-readable storage medium of claim 21
further comprising: requesting from the user whether to update a
search distance preference for merchants; and identifying the at
least one merchant having the incentive based on the updated search
distance preference.
25. The non-transitory computer-readable storage medium of claim 21
further comprising: communicating a code associated with the at
least one incentive to the mobile device, wherein the code is valid
for a predetermined period of time at the corresponding merchant
within the predefined distance.
26. The non-transitory computer-readable storage medium of claim 21
further comprising: determining the geographic location of the
mobile device based on at least one of a triangulation service or a
global positioning service (GPS) of the mobile device, a location
input from the user of the mobile device, a location-dependent
search term input from the user of the mobile device, and a tag
associated with a unique geographic location.
27. The non-transitory computer-readable storage medium of claim 21
further comprising: determining the item based on at least one of a
text input from the user of the mobile device, an audio input from
the user of the mobile device, a machine-readable symbol input from
the user of the mobile device, an image input from the user of the
mobile device, and a video input from the user of the mobile
device.
28. The non-transitory computer-readable storage medium of claim 21
wherein the incentive is generated based on a preference setting of
the user of the mobile device, the preference setting comprising a
user-defined search distance preference.
29. The non-transitory computer-readable storage medium of claim 21
further comprising: receiving attributes of incentives from at
least one merchant within the predefined distance; storing the
attributes of the incentives in a database, wherein the attributes
of the incentives for an item comprises at least one of a name
attribute of the merchant within the predefined distance, a name
attribute of the item, a brand attribute of the item, a model
attribute of the item, a category tag of the item, a sub-category
tag of the item, a financial promotion attribute of the item, and a
financial promotion term attribute of the item.
30. The non-transitory computer-readable storage medium of claim 21
wherein the incentive comprises a coupon, a discount, or a
recommendation.
Description
TECHNICAL FIELD
This application relates to a method and system for determining
targeted incentives based on a user location and activity.
BACKGROUND
With the advent of sophisticated mobile devices, users have instant
access to information when shopping for items. For example, a user
may be able to look up pricing information on his/her mobile device
while noticing the item of interest at a retail store. The mobile
device may access a pricing comparison website that asks the user
to enter the information on the item of interest. Pricing
comparison websites typically use a search engine to collect
pricing information from random online retailers. Unfortunately,
the pricing information conveyed to the user on the mobile device
only includes the price of the item sold at a corresponding
merchant and does not include additional details and information
that may be of interest to the user.
BRIEF DESCRIPTION OF THE DRAWINGS
The present invention is illustrated by way of example, and not by
way of limitation, in the figures of the accompanying drawings in
which:
FIG. 1 is a network diagram depicting a network system, according
to one embodiment, having a client-server architecture configured
for exchanging data over a network;
FIG. 2 is a block diagram illustrating an example embodiment of a
location-based incentive application;
FIG. 3 is a block diagram illustrating an example embodiment of a
location identification module;
FIG. 4 is a block diagram illustrating an example embodiment of an
item identification module;
FIG. 5 is a block diagram illustrating an example embodiment of an
incentive module;
FIG. 6 is a block diagram illustrating an example of attributes of
a data structure for an incentive;
FIG. 7A is a flow chart of an example method for identifying a
targeted incentive;
FIG. 7B is a flow chart of another example method for identifying a
targeted incentive;
FIG. 7C is a flow chart of an example method for expanding a search
of local incentives;
FIG. 8 shows a diagrammatic representation of machine in the
example form of a computer system within which a set of
instructions may be executed to cause the machine to perform any
one or more of the methodologies discussed herein.
DETAILED DESCRIPTION
Although the present invention has been described with reference to
specific example embodiments, it will be evident that various
modifications and changes may be made to these embodiments without
departing from the broader spirit and scope of the invention.
Accordingly, the specification and drawings are to be regarded in
an illustrative rather than a restrictive sense.
In various embodiments, a method and a system offer an incentive to
a user of a mobile device based on a geographic location of the
mobile device and the intent of the user. The geographic location
of the mobile device is determined. The item specified by the user
at the geographic location of the mobile device is determined.
Incentives from local merchants are presented to the user based on
the identified item and the geographic location of the mobile
device. Incentives include and are not limited to promotions,
discounts, sales, rebates, coupons. In another embodiment, the
incentive may also include item recommendations.
FIG. 1 is a network diagram depicting a network system 100,
according to one embodiment, having a client-server architecture
configured for exchanging data over a network. For example, the
network system 100 may be a publication/publisher system 102 where
clients may communicate and exchange data within the network system
100. The data may pertain to various functions (e.g., online item
purchases) and aspects (e.g., managing content and user reputation
values) associated with the network system 100 and its users.
Although illustrated herein as a client-server architecture as an
example, other embodiments may include other network architectures,
such as a peer-to-peer or distributed network environment.
A data exchange platform, in an example form of a network-based
publisher 102, may provide server-side functionality, via a network
104 (e.g., the Internet) to one or more clients. The one or more
clients may include users that utilize the network system 100 and
more specifically, the network-based publisher 102, to exchange
data over the network 114. These transactions may include
transmitting, receiving (communicating) and processing data to,
from, and regarding content and users of the network system 100.
The data may include, but are not limited to, content and user data
such as feedback data; user reputation values; user profiles; user
attributes; product and service reviews and information, such as
pricing and descriptive information; product, service, manufacture,
and vendor recommendations and identifiers; product and service
listings associated with buyers and sellers; auction bids; and
transaction data, among other things.
In various embodiments, the data exchanges within the network
system 100 may be dependent upon user-selected functions available
through one or more client or user interfaces (UIs). The UIs may be
associated with a client machine, such as a client machine 106
using a web client 110. The web client 110 may be in communication
with the network-based publisher 102 via a web server 120. The UIs
may also be associated with a client machine 108 using a
programmatic client 112, such as a client application, or a third
party server 114 hosting a third party application 116. It can be
appreciated in various embodiments the client machine 106, 108, or
third party application 114 may be associated with a buyer, a
seller, a third party electronic commerce platform, a payment
service provider, or a shipping service provider, each in
communication with the network-based publisher 102 and optionally
each other. The buyers and sellers may be any one of individuals,
merchants, or service providers, among other things.
A mobile device 132 may also be in communication with the
network-based publisher 102 via a web server 120. The mobile device
132 may include a portable electronic device providing at least
some of the functionalities of the client machines 106 and 108. The
mobile device 132 may include a third party application 116 (or a
web client) configured communicate with application server 122.
Turning specifically to the network-based publisher 102, an
application program interface (API) server 118 and a web server 120
are coupled to, and provide programmatic and web interfaces
respectively to, one or more application servers 122. The
application servers 122 host one or more publication application
(s) 124. The application servers 122 are, in turn, shown to be
coupled to one or more database server(s) 126 that facilitate
access to one or more database(s) 128.
In one embodiment, the web server 120 and the API server 118
communicate and receive data pertaining to listings, transactions,
and feedback, among other things, via various user input tools. For
example, the web server 120 may send and receive data to and from a
toolbar or webpage on a browser application (e.g., web client 110)
operating on a client machine (e.g., client machine 106). The API
server 118 may send and receive data to and from an application
(e.g., client application 112 or third party application 116)
running on another client machine (e.g., client machine 108 or
third party server 114).
A publication application(s) 124 may provide a number of publisher
functions and services (e.g., listing, payment, etc.) to users that
access the network-based publisher 102. For example, the
publication application(s) 124 may provide a number of services and
functions to users for listing goods and/or services for sale,
facilitating transactions, and reviewing and providing feedback
about transactions and associated users.
FIG. 1 also illustrates a third party application 116 that may
execute on a third party server 114 and may have programmatic
access to the network-based publisher 102 via the programmatic
interface provided by the API server 118. For example, the third
party application 116 may use information retrieved from the
network-based publisher 102 to support one or more features or
functions on a website hosted by the third party. The third party
website may, for example, provide one or more listing, feedback,
publisher or payment functions that are supported by the relevant
applications of the network-based publisher 102.
The network-based publisher 102 may provide a multitude of
feedback, reputation, aggregation, and listing and price-setting
mechanisms whereby a user may be a seller or buyer who lists or
buys goods and/or services (e.g., for sale) published on the
network-based publisher 102.
The application server 122 also includes a location-based incentive
application 130. The location-based incentive application 130
communicates incentives to the mobile device 132 based on the
mobile device 132 location and the intent of the user of the mobile
device 132 as further described below.
FIG. 2 is a block diagram illustrating an example embodiment of a
location-based incentive application 130, which is provided as part
of the network-based publisher 102. The location-based incentive
application 130 has a location identification module 202, an item
identification module 204, and an incentive module 206. The
location identification module 202 determines a geographic location
of the mobile device 132. The item identification module 204
identifies an item specified by the user at the geographic location
of the mobile device 132. The incentive module 206 communicates an
incentive from one or more local merchants based on the identified
item and the geographic location of the mobile device 132. These
modules may be implemented in hardware, firmware, or any
combination thereof.
In one embodiment, the location-based incentive application 130
receives a communication from the mobile device 132. For example,
the communication may include a specification of an item and a
location of the mobile device 132. Based on the specified item and
the location of the mobile device 132, the incentive module 206
consults with the database server 126 and database 128 to determine
and communicate incentives from local merchants to the mobile
device 132.
FIG. 3 is a block diagram illustrating an example embodiment of the
location identification module 202. The location of the mobile
device 132 can be determined in many ways. For example, the mobile
device 132 may be equipped with a Global Positioning Service (GPS)
system that would allow the device to communicate the coordinates
or location of the mobile device 132 to a GPS/triangulation module
302 of the location identification module 202. In another example,
the location of the mobile device 132 may be determined by
triangulation using wireless communication towers and/or wireless
nodes (e.g. wi-fi hotspots) within wireless signal reach of the
mobile device 132. Based on the geographic coordinates, the
GPS/triangulation module 302 of the location identification module
202 can determine the geographic location of the mobile device 132
after consulting a mapping database (not shown). Furthermore, the
general location of the mobile device 132 can be located when the
user of the mobile device 132 logs onto a local internet
connection, for example, at a hotel or coffee shop. The Internet
Protocol address of the network connection at the hotel uniquely
identified by the location of the hotel.
The location identification module 202 may also include a location
input module 306 configured to determine a geographic location of
the mobile device 132 by requesting the user to input an address,
city, zip code or other location information on his/her mobile
device 132. In one embodiment, the user can select a location from
a list of locations or a map on the mobile device 132. For example,
a user on the mobile device 132 inputs the location of the mobile
device 132 via an application or a web browser on the mobile device
132. In another embodiment, the location input module 306 derives
the geographic location of the user by communicating with third
party application using respective APIs (Application Programming
Interface).
The location identification module 202 may also include a
location-dependent search term module 304. The location of the
mobile device 132 can be inferred when the user of the mobile
device 132 requests a search on the mobile device 132 using
location-dependent search terms. For example, a user inputs a
search query on his/her mobile device for "Best Japanese Restaurant
San Jose." The location-dependent search term module 304 consults a
database (not shown) that can determine the geographic location of
the best Japanese restaurant in San Jose. The location-dependent
search term module 304 then infers that the user of the mobile
device 132 is at that geographic location. In one embodiment, the
location-dependent search term module detects the search query term
"San Jose" as a location and infers that the location of the user
is in San Jose irrespective of actually running the search.
The location identification module 202 may also include a tag
module 308 configured to determine the geographic location of the
mobile device 132 based on a tag associated with a unique
geographic location. The tag may include, for example, a barcode
tag (e.g. linear barcode or two dimensional bar code) or a Radio
Frequency Identification (RFID) tag that is associated with a
unique geographic location. For example, the user of the mobile
device 132 may use his/her mobile device 132 to scan the tag placed
at a landmark or store. The tag is uniquely associated with the
geographic location of the landmark or store. Such relationship can
be stored in a database. The tag module 308 can then determine the
geographic location of the mobile device 132 based on the tag after
consulting the database.
FIG. 4 is a block diagram illustrating an example embodiment of an
item identification module 204. The item specified by the user of
the mobile device 132 can be determined in many ways using any of
the following examples of modules: a text identification module
402, an audio identification module 404, a machine-readable symbol
module 406, an image identification module 408, and a video
identification module 410.
The text identification module 402 identifies an item or a category
of an item specified by the user at the mobile device 132 using a
text input from the user at the mobile device 132. For example, the
user may enter the brand and model number of an item the user
wishes to search for at the location of the mobile device 132. The
text identification module 402 can then identify the item by
comparing the brand and model number of the item with a database
containing a catalog of products. In another embodiment, the user
can input a category of the item. For example, the user may be
interested in not a specific digital camera but any brand of
digital camera. As such the user may specify "digital camera" as a
category for searching. The text identification module 402 can then
identify items that correspond to the text input by the user. In
this case, the text identification module 402 identifies items that
match the category of the item input by the user (e.g. all digital
cameras).
In another embodiment, the user can enter the barcode or any other
types of codes associated with an item. The text identification
module 402 can then identify the item by comparing the barcode with
a database containing a catalog of products and their corresponding
barcodes.
The audio identification module 404 identifies an item or a
category of the item as specified by the user at the mobile device
using an audio input from the user at the mobile device. For
example, the user may speak the brand name and model of an item the
user wishes to search for at the location of the mobile device. The
audio identification module 404 includes a speech recognition
system (not shown) that enables the spoken words of the user to be
transcribed into text. In another embodiment, the audio
identification module 404 includes a song recognition system (not
shown) that recognizes the title and author of the song.
The audio identification module 404 then can be used to identify
the specified item by comparing the brand and model number of the
item transcribed from the audio with a database containing a
catalog of products. In another embodiment, the user can speak a
category of the item. For example, the user may be interested in
not a specific digital camera but any brand of digital camera. As
such the user may say "digital camera" to the mobile device as a
category for searching. The audio identification module 402 can
then identify items that correspond to the audio input by the user.
In this case, the text identification module 402 identifies items
that match the category of the item as spoken by the user (e.g.
"digital camera").
The machine-readable symbol module 406 identifies an item by having
the user scan the bar code or any other machine-readable symbol
with his/her mobile device 132 as a machine-readable symbol reader.
For example, the mobile device 132 may include an optical device
(e.g. a lens) configured to capture an image of a bar code on an
item or product. The mobile device 132 may then upload the captured
image to the machine-readable symbol module 406. The
machine-readable symbol module 406 processes the machine-readable
symbol by consulting a database of machine-readable symbols to
match the machine-readable symbol with a corresponding item or
product. The machine-readable symbol module 406 can then identify
the item specified by the user at the mobile device. Based on the
identified item, the machine-readable symbol module 406 can further
determine attributes associated with the item. For example, the
machine-readable symbol module 406 can determine the category,
brand, and other product related or similar to the identified item.
Other identifying and descriptive information related to the
identified item may be returned by the machine-readable symbol
module 406 as well.
The image identification module 408 identifies an item by having
the user take a picture of the item with his/her mobile device 132.
Mobile devices commonly have an optical lens for capturing
pictures. The mobile device 132 may then upload the picture to the
image identification module 408. The image identification module
408 analyzes the picture using an image recognition algorithm (not
shown) to match the uploaded picture with a corresponding image of
an item. The image recognition algorithm consults a database of
images and corresponding items to identify the uploaded picture.
For example, a user may take a picture of a shoe with his/her
mobile device 132. The image identification module 408 recognizes
the shoe and identifies its brand and model, among other
identifying and descriptive information about the item. In another
example, the user may take a picture of a barcode or other item
identifier. The image identification module 408 may recognize and
decode the barcode contained in the image and identify the brand
and model. In certain instances, the image identification module
408 may operate in conjunction with one or more other modules, such
as the machine-readable symbol module 406 to perform image
recognition and identification. In another embodiment, the image
identification module 408 can also determine other products related
or similar to the identified item.
The video identification module 410 is configured to identify an
item by having the user take a video of the item with his/her
mobile device. Mobile devices commonly have an optical lens to
capture video. The mobile device 132 may then upload the video (or
a portion of the video) to the video identification module 408. The
video identification module 410 analyzes the frames of the video
using an image recognition algorithm (not shown) to match a frame
of the video with a corresponding image of an item. The image
recognition algorithm consults a database of images and
corresponding items to identify the uploaded video. For example, a
user may take a video with his/her mobile device of a shoe worn by
someone walking. The video identification module 410 recognizes the
shoe and identifies its brand and model, among other identifying
and descriptive information about the item. In another embodiment,
the video identification module 410 can also determine other
products related or similar to the identified item.
FIG. 5 is a block diagram illustrating an example embodiment of the
incentive module 206 that may used to execute the processes
described herein. The incentive module 206 includes a local
merchant module 502, an item category module 504, an incentive
matching module 506, a user preference module 508, an incentive
receiver module 510, an incentive code generator module 512, and a
communication module 514.
The local merchant module 502 identifies at least one local
merchant having at least one incentive based on the geographic
location of the mobile device 132 as determined by the location
identification module 202. A local merchant may be a merchant or
retailer that is located within a predefined distance from the
geographic location of the mobile device 132. In one embodiment,
the local merchant module 502 identifies at least one local
merchant with at least one incentive based on an updated search
distance preference as specified in the user preference module
508.
It should be noted that the incentive of the local merchant may or
may not correspond to the item identified by the user. For example,
a local merchant may feature a special sale on shoes while
identified item corresponds to a digital camera. Once all local
merchants having incentives are identified based on the geographic
location of the mobile device 132 (using a database of incentives),
the incentive match module 506 filters all local merchants based on
the identified item. In the previous example, the local merchant
featuring a sale on shoes may be filtered out from the search
result.
The item category module 504 determines a category of the item
specified by the user and identified by item identification module
204. For example, the user may specify a particular digital camera.
The item category module 504 determines that the item specified by
the user falls into the category of electronics and the subcategory
of cameras.
The incentive match module 506 determines whether the identified
item specified by the user corresponds to an item identified in at
least one incentive of at least one local merchant as determined by
the local merchant module 502. For example, a user specifies an
item with his/her mobile device. The item is identified as a
specific digital camera. The item identification module 204
generates the brand, model number, color, and other attributes of
the specified digital camera. The local merchant module 502
identifies merchants with incentives local to the geographic
location of the mobile device 132. The incentive match module 506
matches local merchants with incentives (sale or discount) on the
specific digital camera.
In another embodiment, the incentive match module 506 determines
whether the category of the item identified by the user corresponds
to a category of items as determined by item category module 504
and identified in at least one incentive of at least one local
merchant. For example, a user specifies an item with his/her mobile
device 132. The item is identified as a specific digital camera.
The item identification module 204 generates the brand, model
number, color, and other attributes of the specified digital
camera. The item category module 504 determines the category of the
identified item: electronics. The local merchant module 502
identifies merchants with incentives local to the geographic
location of the mobile device 132. The incentive match module 506
matches local merchants with incentives (sale or discount) on
electronics or categories related to the digital camera.
The user preference module 508 provides user-defined preferences
used in the process of determining local merchants or brands or
category of the items. In one embodiment, the user preference
module 508 allows a user to update a search distance preference for
local merchants. For example, the user may wish to decrease the
radius of the distance preference in a downtown area of a city.
Conversely, the user may wish to increase the radius of the
distance preference in a suburban or rural area of a city. In
another embodiment, user preference module 508 may also allow the
user to specify favorite brands of items or favorite merchants or
retailers.
The incentive code module 512 generates a code associated with at
least one incentive selected by the user at the mobile device 132.
The code may be valid for a predetermined period of time at the
corresponding local merchant. For example, a user selects a coupon
from a local merchant on his/her mobile device 132. The incentive
code module 512 generates a code associated with the coupon. The
code is communicated to the mobile device 132 of the user. The user
takes the code to the corresponding local merchant to redeem the
discount. The code can be redeemed at the local merchant by showing
or telling the code to a cashier at the checkout register of the
local merchant. The cashier may then enter the code at the checkout
register to determine the validity of the code and appropriately
apply the discount or promotion. The code can also be redeemed by
displaying a machine-readable code such as a bar code on a screen
of the mobile device 132. The user then displays the bar code to
the cashier at the checkout register who can scan the bar code to
determine the validity of the code and appropriately apply the
discount or promotion.
In one embodiment, the code may be valid for a predetermined period
of time (e.g. one day, one week, etc. . . . ). In another
embodiment, the generated code may be uniquely associated with the
user of the mobile device 132 and may expire immediately upon
redeeming the coupon.
The communication module 514 communicates one or more incentives of
the identified item from at least one local merchant to the mobile
device 132. For example, a list of local merchants within a preset
distance radius (e.g. one mile) of the mobile device 132 is
displayed. The list of local merchants may include a sale or
discount on the item identified by the user of the mobile device
132. The list may also include a list of recommended merchants
(having an incentive on the identified item) that are located
beyond the preset distance radius.
In another embodiment, the communication module 514 communicates
one or more incentives of the identified category of the items from
at least one local merchant to the mobile device 132. For example,
a list of local merchants within a preset distance radius (e.g. a
block) of the mobile device 132 is displayed. The list of local
merchants may include a sale or discount on similar or related
items to the identified item specified by the user of the mobile
device 132. The list may also include a list of recommended
merchants (having an incentive on similar items to the identified
item) that are located beyond the preset distance radius.
The incentive receiver module 510 collects attributes of incentives
from merchants and stores the attributes of the incentives in an
incentive database. An example of a data structure of the incentive
database is further described in FIG. 6.
FIG. 6 is a block diagram illustrating attributes of an example of
a data structure of an incentive. In one embodiment, the data
structure of the incentive database includes attributes of the
incentives for an item. For example, the attributes include a name
attribute of the merchant 602, a name attribute of the item 604, a
brand attribute of the item 606, a model attribute of the item 608,
a category tag of the item 610, a sub-category tag of the item 612,
a financial promotion attribute of the item 614, and a financial
promotion term attribute of the item 616.
The merchant name attribute 602 includes the name of the local
merchant (e.g. Joe's Electronic Shop). The item name attribute 604
includes the name of an item (e.g. digital camera XYZ D001). The
brand attribute 606 includes the brand name of the item (e.g. brand
XYZ). The model attribute 608 includes the model number of the item
(e.g. D001). The category tag 610 includes a category metadata
associated with the item (e.g. personal electronics). The
sub-category tag 612 includes a sub-category metadata associated
with the item (e.g. digital camera). The financial promotion
attribute 614 includes the sale or discount associated with the
item (e.g. 40% all digital cameras, or 20% all brand XYZ digital
cameras). The financial promotion term 616 includes the terms of
the sale or discount associated with the item (e.g. discount
expires on xx/xx/xxxx, discount expires one week from today, or
discount valid today only).
FIG. 7A is a flow chart of an example method for identifying a
targeted incentive. At 702, the location identification module 202
of the location-based incentive application 130 determines the
geographic location of a mobile device of a user. At 704, the item
identification module 204 of the location-based incentive
application 130 identifies an item specified by the user at the
geographic location of the mobile device 132. At 706, the local
merchant module 502 of the incentive module 206 determines local
merchants to the geographic location of the mobile device 132 with
at least one incentive. At 708, the incentive match module 506 of
the incentive module 206 of the location-based incentive
application 130 determines whether the identified item as specified
by the user corresponds to an item identified in at least one
incentive of the local merchants as determined at operation 706. At
710, the communication module 514 of the incentive module 206 of
the location-based incentive application 130 communicates a list of
local merchants with incentives for the identified item to the
mobile device 132.
FIG. 7B is a flow chart of another example method for identifying a
targeted incentive. At 712, if there are no local merchants having
incentives on the identified item, the item category module 504 of
the incentive module 206 of the location-based incentive
application 130 determines a category of the identified item. At
714, the incentive match module 506 of the incentive module 206 of
the location-based incentive application 130 determines whether a
category of the identified item as specified by the user
corresponds to a category of items identified in at least one
incentive of the local merchants as determined at operation 706. At
716, the communication module 514 of the incentive module 206 of
the location-based incentive application 130 communicates a list of
local merchants with incentives on similar or related items from
the same category of the identified item to the mobile device
132.
FIG. 7C is a flow chart of an example method for expanding a search
of local incentives. At 718, the communication module 514 of the
incentive module 206 of the location-based incentive application
130 communicates that the incentive match module 506 of the
incentive module 206 of the location-based incentive application
130 cannot find any incentives from local merchants related to the
identified item to the mobile device 132. At 720, the incentive
module 206 may offer the user to expand or increase the distance
radius preference for local merchants in the user preference module
508. At 722, the user preference module 508 may be updated to
reflect a new distance radius preference when searching for local
merchants with incentives.
FIG. 8 shows a diagrammatic representation of machine in the
example form of a computer system 800 within which a set of
instructions may be executed causing the machine to perform any one
or more of the methodologies discussed herein. In alternative
embodiments, the machine operates as a standalone device or may be
connected (e.g., networked) to other machines. In a networked
deployment, the machine may operate in the capacity of a server or
a client machine in server-client network environment, or as a peer
machine in a peer-to-peer (or distributed) network environment. The
machine may be a personal computer (PC), a tablet PC, a set-top box
(STB), a Personal Digital Assistant (PDA), a cellular telephone, a
web appliance, a network router, switch or bridge, or any machine
capable of executing a set of instructions (sequential or
otherwise) that specify actions to be taken by that machine.
Further, while only a single machine is illustrated, the term
"machine" shall also be taken to include any collection of machines
that individually or jointly execute a set (or multiple sets) of
instructions to perform any one or more of the methodologies
discussed herein.
The example computer system 800 includes a processor 802 (e.g., a
central processing unit (CPU), a graphics processing unit (GPU) or
both), a main memory 804 and a static memory 806, which communicate
with each other via a bus 808. The computer system 800 may further
include a video display unit 810 (e.g., a liquid crystal display
(LCD) or a cathode ray tube (CRT)). The computer system 800 also
includes an alphanumeric input device 812 (e.g., a keyboard), a
user interface (UI) navigation device 814 (e.g., a mouse), a disk
drive unit 816, a signal generation device 818 (e.g., a speaker)
and a network interface device 820.
The disk drive unit 816 includes a machine-readable medium 822 on
which is stored one or more sets of instructions and data
structures (e.g., software 824) embodying or utilized by any one or
more of the methodologies or functions described herein. The
software 824 may also reside, completely or at least partially,
within the main memory 804 and/or within the processor 802 during
execution thereof by the computer system 800, the main memory 804
and the processor 802 also constituting machine-readable media.
The software 824 may further be transmitted or received over a
network 826 via the network interface device 820 utilizing any one
of a number of well-known transfer protocols (e.g., HTTP).
While the machine-readable medium 822 is shown in an example
embodiment to be a single medium, the term "machine-readable
medium" should be taken to include a single medium or multiple
media (e.g., a centralized or distributed database, and/or
associated caches and servers) that store the one or more sets of
instructions. The term "machine-readable medium" shall also be
taken to include any medium that is capable of storing, encoding or
carrying a set of instructions for execution by the machine and
that cause the machine to perform any one or more of the
methodologies of the present invention, or that is capable of
storing, encoding or carrying data structures utilized by or
associated with such a set of instructions. The term
"machine-readable medium" shall accordingly be taken to include,
but not be limited to, solid-state memories, optical media, and
magnetic media.
The Abstract of the Disclosure is provided to comply with 37 C.F.R.
.sctn.1.72(b), requiring an abstract that will allow the reader to
quickly ascertain the nature of the technical disclosure. It is
submitted with the understanding that it will not be used to
interpret or limit the scope or meaning of the claims. In addition,
in the foregoing Detailed Description, it can be seen that various
features are grouped together in a single embodiment for the
purpose of streamlining the disclosure. This method of disclosure
is not to be interpreted as reflecting an intention that the
claimed embodiments require more features than are expressly
recited in each claim. Rather, as the following claims reflect,
inventive subject matter lies in less than all features of a single
disclosed embodiment. Thus the following claims are hereby
incorporated into the Detailed Description, with each claim
standing on its own as a separate embodiment.
* * * * *
References